BSH Turkey boosts productivity with Industrial Edge

Siemens has digitalized the production of plastic tubs for washing machines at BSH Turkey using Industrial Edge Technology.

BSH Home Appliances

Production of plastic tub for washing machines at BSH Turkey, plastic tubs, autonomous vehicle for logistics

BSH Home Appliances Türkiye is a leading manufacturer of household appliances in Turkey and part of the global BSH Hausgeräte GmbH group. The company has been active in the country since the mid-1990s and produces appliances under well-known brands such as Bosch, Siemens, Gaggenau, and Profilo.

Headquartered in Istanbul, BSH Türkiye operates five production sites as well as one of the company’s largest global R&D centers in Çerkezköy. From there, innovative and energy-efficient household appliances are developed, manufactured, and exported to more than 150 countries.

Enhancing transparency and efficiency in production

Imagine a state-of-the-art washing machine tub production line, yet its full potential remains untapped. This was precisely the situation BSH faced. Despite its capabilities, the company grappled with several critical challenges. Initially, system transparency was severely limited, primarily due to non-standardized shop floor communication protocols that hindered a comprehensive overview of production and made crucial data inaccessible.

Furthermore, identifying the root causes of quality issues proved to be a complex and time-consuming endeavor, as process parameters had to be meticulously collected and analyzed for each product individually – a significant drain on resources. These obstacles led to unnecessary downtime and quality defects, which ultimately impeded overall operational efficiency and productivity.

Production of plastic tub for washing machines at BSH Turkey, interior of a large plastic injection molding machine.

BSH Turkey plastic tub production, man with tablet

Therefore, BSH's clear objective was to significantly enhance traceability, productivity, and line performance. Concurrently, a drastic reduction in quality issues and energy consumption was paramount. At its core, the goal was to swiftly and precisely identify the root causes of quality issues to optimize production in a sustainable way and unlock the line's full potential.

Customer success story

BSH_Turkey_plastic_tub_production_04, screen with software

Industrial Edge drives data integration and production optimization

To address these critical challenges and transform BSH's production line, Siemens implemented a comprehensive solution for BSH based on its Industrial Edge technologies. This enabled seamless data integration and advanced analytics across the production line. Data was efficiently collected using Industrial Edge apps, structured as an OPC UA model within the Industrial Information Hub (IIH), and then published to BSH’s MES system. Crucially, a unique ID was generated and archived for each produced tub, enabling consistent linking of process parameters and establishing full, precise traceability – a key objective.

To further enhance operational performance, Siemens deployed powerful applications including Performance Insight, Energy Manager, Notifier, and Anomaly Detection. These Industrial Edge apps empowered BSH to identify inefficiencies, optimize energy consumption, and detect irregularities in injection machines early. The intelligent combination of standard Siemens Industrial Edge apps with custom-developed applications provided efficient access to shop floor data, improved communication with IT systems, and significantly increased transparency and overall production efficiency for BSH.

Screenshot of Siemens Industrial Management screen

Industrial Edge apps helped us to easily monitor and analyze our production and consumption indicators instantly and historically, improve them when necessary and easily add our increasing needs to the system.

Sefa Boyacı, IT Industry 4.0 Projects Manager, BSH Turkey

Benefits for BSH

Data access

System transparency was increased by collecting data with Industrial Edge apps, structuring it as an OPC UA model in the Industrial Information Hub (IIH), and publishing it to the MES for better analysis and optimization.

Identifying quality issues

Creating and archiving a unique ID for each product and linking it to all relevant process data, enabling clear analysis of the root causes of quality issues and their origins.

Higher OEE, lower energy consumption

OEE increased by 20%, energy consumption reduced by 25%, less downtime and minimized quality issues: This was achieved by using the apps Performance Insight, Energy Manager, Notifier, and Anomaly Detection.